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# pytorch-cifar10 | ||
www.kaggle.com/c/cifar-10 | ||
# ResNet on Cifar10 | ||
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[kaggle-cifar10](http://www.kaggle.com/c/cifar-10) | ||
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## 环境 | ||
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- python3.9 | ||
- PyTorch version: 2.2.0+cpu | ||
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## 运行 | ||
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#### 1.数据集 | ||
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按照说明文档中的数据集结构(使用d2l的方法)处理好数据放置于'./data'中。 | ||
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#### 2.训练模型 | ||
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运行'cifar10-train.ipynb'中代码即可,其中包含resnet18(修改), resnet56。 | ||
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#### 3.测试模型 | ||
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导入model中保存的模型,使用'cifar10-train.ipynb'最后部分的预测生成'submisson.csv',上传kaggle评分。 | ||
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## 效果 | ||
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#### resnet56 | ||
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测试准确率达到92.46% | ||
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#### resnet18(修改) | ||
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测试准确率达到89.94% |
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